Objects in three dimensional space are viewed by humans as the image they project onto a two dimensional imaging surface. It is such projected two dimensional images that are processed to extract relevant three dimensional motion information. This processing of the two dimensional image data to extract three dimensional motion information is generally performed in two stages. In the first stage, the two dimensional image motion is extracted from sequences of images. Image motion is typically respresented as a field of two dimensional velocity vectors, one for each small region of the visual field. These two dimensional velocity vectors are known as optical flow vectors. Sets of these vectors form optical flow fields. In the second stage, the extracted image motion is interpreted in terms of objects and surfaces in the three dimensional world.
Analysts have been quite successful in performing the first stage. In particular, they have been successful in extracting optical flow fields for machine vision application. Unfortunately, analysts have not met with equal success regarding the second interpretive stage. Efforts to date have only been able to determine minimal three dimensional information and have only revealed data for greatly specialized circumstances.